5 papers · 1 filter
Conditional Flow Matching for Cross-Field MRI Harmonisation
Baris Imre, Aram Salehi, Levente Baljer +3
Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data across sites. We address cross-fi…
Enhancing Implicit Neural Representations with Image Feature Embedding for Unsupervised Cardiac Cine MRI Reconstruction
Donghang Lyu, Marius Staring, Yiming Dong +3
Cardiac cine Magnetic Resonance Imaging (MRI) is a critical diagnostic tool that provides dynamic insights for radiologists. To accelerate acquisition, under-sampled k-space data i…
CRUNet-MR-Univ: A Foundation Model for Diverse Cardiac MRI Reconstruction
Donghang Lyu, Marius Staring, Hildo Lamb +1
In recent years, deep learning has attracted increasing attention in the field of Cardiac MRI (CMR) reconstruction due to its superior performance over traditional methods, particu…
KP-INR: A Dual-Branch Implicit Neural Representation Model for Cardiac Cine MRI Reconstruction
Donghang Lyu, Marius Staring, Mariya Doneva +2
Cardiac Magnetic Resonance (CMR) imaging is a non-invasive method for assessing cardiac structure, function, and blood flow. Cine MRI extends this by capturing heart motion, provid…
UPCMR: A Universal Prompt-guided Model for Random Sampling Cardiac MRI Reconstruction
Donghang Lyu, Chinmay Rao, Marius Staring +4
Cardiac magnetic resonance imaging (CMR) is vital for diagnosing heart diseases, but long scan time remains a major drawback. To address this, accelerated imaging techniques have b…